The AI Specialist SA team builds technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey while adopting GenAI/ML and Agentic technologies across their organisation.
You’ll manage the overall technical relationship between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their challenging GenAI/ML and Agentic projects.
Internally, you will be the voice of the customer, sharing their needs with regard to their usage of our services impacting the roadmap of AWS GenAI/ML and Agentic features.
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Responsible for using algorithms to mine, identify, and predict risks and low-quality merchants, products, and creators in e-commerce scenarios, and assist businesses in managing and controlling them.
Responsible for using algorithms to identify events and behaviors that affect product experience and efficiency, and building data models to help create a favorable ecosystem and support business operations.
Participate in building data for various entities such as e-commerce live streaming/video, products, merchants, and creators, building large-scale network/feature sequence models to support business scenarios such as content understanding, multimodal representation, community mining, and solve problems related to products, live streaming, and video management, and provide support for them.
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We are seeking a highly skilled and visionary Machine Learning Lead to lead the design, development, and deployment of cutting-edge AI/ML solutions using Azure Machine Learning , OpenAI APIs , and Generative AI technologies .
Experience working with ML platforms such as CML, Spark MLlib, and Python ML libraries (scikit‑learn, XGBoost), including model deployment.
Exposure to building enterprise‑grade applications using large language models and frameworks (e.g., Hugging Face, LangChain).
Design and develop highly scalable, Real time systems using Hadoop ecosystem components(Iceberg, Spark, Ozone, Trino, Hive, Ranger, Kafka, Flink and Nifi)
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Support the achievement of sales targets by developing and maintaining a healthy pipeline and guiding customers through end-to-end sales cycles, from discovery through to agreement;
Create detailed account plans and territory strategies in partnership with internal teams, while maintaining accurate forecasting using CRM tools;
Collaborate with customers to identify and qualify high-impact AI use cases aligned to their business priorities and strategic objectives.
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